> What about a pan sensor created by taking an RGB sensor and removing the filter so it's producing an image with 3x the resolution but in pan? This got me thi

> What about a pan sensor created by taking an RGB sensor and removing the filter so it's producing an image with 3x the resolution but in pan? This got me thinking about how subtle and slippery the concept of "resolution" is. The relationship is not strictly 3x; an ideally demosaiced Bayer filtered image still contains some information at the original capture resolution, because R, G, and B are correlated in nontrivial ways. Nyquist is a nice and simple result for the special case where nothing can be predicted about the original function, measurements are assumed to be perfect, and the criterion for reconstruction is "exact" - but in the general case of "recovering information, more is better" even a simple interpolation procedure with tame priors like "luminance exists" might perform so much better than the naive approach that we'd be silly not to use it. Even the Nyquist frequency itself is less fundamental than it first appears; a less well known result is that a function can also be perfectly recovered if sampled at half the Nyquist frequency, if the slope is captured as well as the value. In other words you can losslessly convert a 2MP image into a 1M value+slope data matrix and back. What resolution is it? Depends on your point of view.